Students Can Exhibit Discretionary Responding to Texts Social Media Messages During Class: Fact or Fiction?
Bibliographic record
Abstract
Terms such as ‘compulsion’ and ‘addiction’ are often used when describing young adults’ response behaviors regarding texts and messages. Purpose of the Research: The present study documents response patterns for texts and messages in a higher education classroom context. Both the number of texts and messages responded to and the time taken between receipt and response were examined. These measures, as well as perceptions about multitasking and learning, were examined with respect to performance for lecture content. Students were assigned to either a texting or social media message condition. Within each of these conditions, students were either instructed to respond to texts/messages immediately or at their own discretion. Principal Results: Consistent with characterizations of habits/compulsions, the majority of participants in all conditions responded to most of the individual texts/messages. In no condition did all participants respond to all of the texts/messages. Students in the discretionary texting condition took longer to reply to texts/messages than those in the immediate social media condition for the vast majority of texts/messages received. Higher performance scores were found for test items not associated with the arrival of texts/messages. Students acknowledged some potential for multitasking to impact learning, however, these perceptions were not related to the volume or timing of text/message responses. Major Conclusions: This study identifies that students responding to texts/messages in the educational context is more complex than a simple habitual behaviour and that the pervasiveness may make the behavior a challenge even in live lecture contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".